Systems and methods for media privacy

ABSTRACT

A system comprises a picture and metadata captured by a content capture system; a recognizable characteristic datastore configured to store recognizable characteristics of different users; a module configured to identify a time and a location associated with the picture based on the metadata, and to identify one or more potential target systems within a predetermined range of the location at the time; a characteristic recognition module configured to retrieve the recognizable characteristics of one or more potential users associated with the potential target systems, and evaluate whether the picture includes one or more representations of at least one actual target user from the potential users based on the recognizable characteristics of the potential users; a distortion module configured to distort a feature of the representations of the least one actual target user in response to the determination; a communication module configured to communicate the distorted picture to a computer network.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a continuation of U.S. patent applicationSer. No. 17/857,431 filed Jul. 5, 2022 and entitled “Systems and Methodsfor Media Privacy,” which is a continuation of U.S. patent applicationSer. No. 16/144,932 filed Sep. 27, 2018 and entitled “Systems andMethods for Media Privacy,” now U.S. Pat. No. 11,379,953, which is acontinuation of U.S. patent application Ser. No. 15/921,545 filed Mar.14, 2018 and entitled “Systems and Methods for Media Privacy,” now U.S.Pat. No. 10,089,723, which is a continuation of U.S. patent applicationSer. No. 15/201,015 filed Jul. 1, 2016 and entitled “Systems and Methodsfor Media Privacy,” now U.S. Pat. No. 9,990,700, which claims priorityto U.S. Provisional Patent Application Ser. No. 62/188,033 filed Jul. 2,2015 and entitled “Media Privacy,” which are incorporated herein byreference.

COPYRIGHT NOTICE

A portion of the disclosure of this patent document contains materialwhich is subject to copyright protection. The copyright owner has noobjection to the facsimile reproduction by anyone of the patent documentor the patent disclosure, as it appears in the Patent and TrademarkOffice patent file or records, but otherwise reserves all copyrightrights whatsoever.

BACKGROUND Technical Field

Embodiments of the present inventions relate generally to the field ofmedia. More specifically, embodiments of the present inventions relateto media privacy.

Description of Related Art

The Internet has provided platforms (e.g., Facebook, Instagram, etc.)for posting pictures and other media that are accessible by almostanyone, anywhere, which can raise a variety of privacy issues. Moreover,digital cameras are becoming more prevalent every day, and they areoften included in mobile devices (e.g., smartphones, tablets,smartglasses, etc.), which can make it difficult for individuals to evenbe aware that their picture has been taken. Thus, for example, picturesmay be taken of an individual and posted on a social media systemwithout the individual ever have been made aware that their pictures wastaken, let alone that it had been posted on the Internet.

SUMMARY

The Internet has provided platforms (e.g., Facebook, Instagram, etc.)for posting pictures and other media that are accessible by almostanyone, anywhere, which raises a variety of privacy issues. Moreover,digital cameras are becoming more prevalent every day, and they areoften included in mobile devices (e.g., smartphones, tablets,smartglasses, etc.), which can make it difficult for individuals to evenbe aware that their picture has been taken. Thus, for example, picturesmay be taken of an individual and posted on a social media systemwithout the individual ever have been made aware that their pictures wastaken, let alone that it had been posted on the Internet.

Some embodiments described herein include systems and methods for mediaprivacy. For example, a content capture system (e.g., smartphone) maycapture a picture of one or more individuals, and store the picturelocally on the content capture system. The content capture system mayprovide the picture to a content processing server that recognizes atleast some of the individuals in the picture, and determines whether todistort a representation of the recognized individuals based onassociated privacy preferences. For example, the content processingsystem may blur the face of one individual, but not the others, based ontheir respective privacy preferences. The content processing system mayprovide the distorted picture to the content capture system, and thecontent capture system may replace the original picture with thedistorted picture.

In various embodiments, a system comprises a picture and associatedmetadata, the picture and the associated metadata captured by a contentcapture system. A recognizable characteristic datastore may beconfigured to store a plurality of recognizable characteristics, each ofthe plurality of recognizable characteristics associated with adifferent user. A location identification module may be configured toidentify a location based on the associated metadata, and identify a setof potential target systems within a predetermined range of thelocation. A characteristic recognition module may be configured tocompare a set of recognizable characteristics of the plurality ofrecognizable characteristics with the picture, each recognizablecharacteristic of the set of recognizable characteristics associatedwith a different potential target user of a corresponding potentialtarget system, and determine whether the picture includes one or morerepresentations of at least one actual target user of the potentialtarget users based on the comparison. A distortion module may beconfigured to distort a feature of each of the one or morerepresentations of the least one actual target user in response to thedetermination, and a communication module may be configured to providethe distorted picture to the first content capture system.

In some embodiments, at least a portion of the plurality of recognizablecharacteristics comprises a set of images. In some embodiments, at leasta portion of the plurality of recognizable characteristics comprises oneor more features derived from a set of images. In some embodiments, thefeature comprises one or more facial features. In some embodiments, atleast a portion of the plurality of recognizable characteristicscomprises a wearable item.

In some embodiments, the location comprises a time and location.

In some embodiments, the system further comprises a profile generationmodule configured to determine distortion preferences for the at leastone actual target user, wherein the distortion module configured todistort the feature comprises the distortion module configured todistort the feature based on the distortion preferences.

In some embodiments, the distortion module configured to distort thefeature comprises the distortion module configured to blur the feature.

In various embodiments, a method comprises receiving a picture andassociated metadata, the picture and the associated metadata captured bya content capture system. A plurality of recognizable characteristicsmay be stored, each of the plurality of recognizable characteristicsassociated with a different user. A location may be identified based onthe associated metadata. A set of potential target systems may beidentified within a predetermined range of the location. A set ofrecognizable characteristics of the plurality of recognizablecharacteristics may be compared with the picture, each recognizablecharacteristic of the set of recognizable characteristics associatedwith a different potential target user of a corresponding potentialtarget system. The method may further comprise determining whether thepicture includes one or more representations of at least one actualtarget user of the potential target users based on the comparison. Afeature of each of the one or more representations of the least oneactual target user may be distorted in response to the determination.The distorted picture may be provided to the first content capturesystem.

In some embodiments, at least a portion of the plurality of recognizablecharacteristics comprises a set of images. In some embodiments, at leasta portion of the plurality of recognizable characteristics comprises oneor more features derived from a set of images. In some embodiments, thefeature comprises one or more facial features. In some embodiments, atleast a portion of the plurality of recognizable characteristicscomprises a wearable item.

In some embodiments, the location comprises a time and location.

In some embodiments, the method further comprises determining distortionpreferences for the at least one actual target user, wherein thedistorting the feature comprises the distorting the feature based on thedistortion preferences.

In some embodiments, the distorting the feature comprises blurring thefeature.

In various embodiments, a non-transitory computer readable mediumcomprises executable instructions, the instructions being executable bya processor to perform a method, the method comprising receiving apicture and associated metadata, the picture and the associated metadatacaptured by a content capture system. A plurality of recognizablecharacteristics may be stored, each of the plurality of recognizablecharacteristics associated with a different user. A location may beidentified based on the associated metadata. A set of potential targetsystems may be identified within a predetermined range of the location.A set of recognizable characteristics of the plurality of recognizablecharacteristics may be compared with the picture, each recognizablecharacteristic of the set of recognizable characteristics associatedwith a different potential target user of a corresponding potentialtarget system. The method may further comprise determining whether thepicture includes one or more representations of at least one actualtarget user of the potential target users based on the comparison. Afeature of each of the one or more representations of the least oneactual target user may be distorted in response to the determination.The distorted picture may be provided to the first content capturesystem.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a block diagram illustrating a content privacy networksystem according to some embodiments.

FIG. 2 depicts a block diagram illustrating details of a content capturesystem according to some embodiments.

FIG. 3 depicts a block diagram illustrating details of a target systemaccording to some embodiments.

FIG. 4 depicts a block diagram illustrating details of a contentprocessing system according to some embodiments.

FIG. 5 depicts a flowchart illustrating a method of distorting a contentitem according to some embodiments.

FIG. 6 depicts a flowchart illustrating a method of distorting a contentitem and posting the distorted content item to a third-party systemaccording to some embodiments.

FIG. 7 depicts a flowchart illustrating a method of operation of acontent processing system for distorting a content item according tosome embodiments.

FIG. 8 depicts a block diagram illustrating details of a computingdevice according to some embodiments.

DETAILED DESCRIPTION

The Internet has provided platforms (e.g., Facebook, Instagram, etc.)for posting pictures and other media that are accessible by almostanyone anywhere, which raises a variety of privacy issues. Moreover,digital cameras are becoming more prevalent, as they are now typicallyincluded in mobile devices (e.g., smartphones, tablets, smartglasses,etc.), which makes it more difficult for individuals to even be awarethat their picture has been taken. Thus, for example, pictures may betaken of an individual and sometimes even posted on a social mediasystem without the individual ever have been made aware that theirpictures was taken, let alone publicized on the Internet.

Some embodiments described herein include systems and methods for mediaprivacy. For example, a content capture system (e.g., smartphone) maycapture a picture of one or more individuals, and store the picturelocally on the content capture system. The content capture system mayprovide the picture to a content processing server that recognizes atleast some of the individuals in the picture, and determines based onuser preferences whether to distort a representation of the recognizedindividuals based on associated privacy preferences. For example, thecontent processing system may blur the face of one individual, but notthe others, based on their respective privacy preferences. The contentprocessing system may provide the distorted picture to the contentcapture system, so that the content capture system may replace theoriginal picture with the distorted picture. In other embodiments, thecontent capture system may cooperate with the content processing systemto determine whether to distort the representation of the recognizedindividuals before the picture is posted on a social media website. Inother embodiments, the social media system may cooperate with thecontent processing system to determine whether to distort therepresentation of the recognized individuals before the picture isposted on a social media website. Other embodiments and applications arealso possible.

FIG. 1 depicts a block diagram illustrating a content privacy networksystem 100 according to some embodiments. The system 100 includescontent capture systems 102-1 to 102-n (individually, the contentcapture system 102, collectively, the content capture systems 102),target systems 104-1 to 104-n (individually, the target system 104,collectively, the target systems 104), a content processing system 106,third-party systems 108-1 to 108-n (individually, the third-party system108, collectively, the third-party systems 108), and a communicationnetwork 110.

The content capture systems 102 may be configured to capture, store,provide, and receive content items (e.g., pictures, images, video,audio, etc.) and associated metadata (e.g., location information, timeinformation, content capture system 102 information, etc.). For example,the content capture system 102 may capture a picture of one or moretargets (e.g., individuals, buildings, structures, etc.) along with alocation (e.g., geographic coordinates, street address, city, town,etc.) and a time (e.g., time of day, date, etc.) the picture wascaptured, and an identifier (e.g., a UID) of the content capture system102. In some embodiments, functionality of the content capture systems102 may be performed by one or more mobile devices (e.g., smartphones,cell phones, smartwatches, tablet computers, smartglasses, or the like),cameras, desktop computers, laptop computers, workstations, or the like.

The target systems 104 may be configured to identify time and locationinformation for associated devices and/or users. For example, theassociated devices and/or users may include potential and actual targetusers, as well as their associated devices (e.g., smartphones). In someembodiments, the target systems 104 may provide (e.g., broadcast)location coordinates (e.g., GPS coordinates, Wi-Fi-based coordinates,cellular tower-based coordinates, etc.) at various predeterminedintervals (e.g., every 15 seconds, every minute, etc.). In variousembodiments, functionality of the target systems 104 may be performed byone or more mobile devices (e.g., smartphones, cell phones,smartwatches, tablet computers, smartglasses, or the like), desktopcomputers, laptop computers, workstations, or the like. In variousembodiments, the target systems 104 include some or all of thefunctionality of a content capture system 102. Likewise, in someembodiments, the content capture systems 102 may include some or all ofthe functionality of the target systems 104.

The content processing system 106 may be configured to evaluate thecontent relative to target user preferences, and to distort, orotherwise modify, content items based on those preferences. For example,the content processing system 106 may distort particular features (e.g.,facial features) of individuals captured in a content item, if thepreferences of the individuals are set to distort. In some embodiments,functionality of the content processing system 106 may be performed byone or more workstations, desktop computers, laptop computers, mobiledevices, or the like.

In some embodiments, the content processing system 106 receives acontent item and associated metadata, identifies a set of potentialtarget users that may be represented in the content item (e.g., based onlocation and time information), identifies a set of actual target usersrepresented in the content item, and, based on privacy preferences ofthe actual target users, distort their representation within the contentitem. For example, a particular user's privacy preference may indicatethat their face should be blurred, or otherwise anonymized, in all orsome pictures (e.g., pictures captured by unknown or untrusted users,captured in particular locations, etc.), but not in other pictures(e.g., pictures captured by known or trusted users, captured in trustedlocations, etc.). This system may, for example, improve user privacy bypreventing other systems and users from posting pictures of the users ortaking other actions on the content without their permission.

As used in this paper, a potential target user may be any user that maypotentially be represented within a content item. For example, potentialtarget users may include users within a predetermined distance (e.g., 60feet) of a location the content item was captured at or within aparticular time period of the time the content item was captured. Asfollows, actual target users may be users selected from the potentialtarget users that are represented within the content item.

In some embodiments, the content processing system 106 identifies actualtarget users based on recognizable characteristics of potential targetusers. For example, users may submit several images (e.g., six pictures)of their face captured from several angles. In some embodiments, imagesare submitted during account registration. The content processing 106may generate a recognizable characteristic based on the pictures. Forexample, the recognizable characteristic may be the set of imagesthemselves, a composite image generated from the set of images, or oneor more other recognizable characteristics that may be used to identifya user. In some embodiments, the content processing system 106 may usethe recognizable characteristics to perform facial recognition oncontent items to identify actual target users.

The third-party systems 108 may be configured to post (or otherwisepublish) content items, including distorted content items. For example,the third-party systems 108 may comprise social media systems (e.g.,Facebook, Instagram, Pinterest, Snapchat, etc.), blogs, email systems,instant messaging systems, and the like. In some embodiments,functionality of the third-party systems 108 may be performed by one ormore workstations, desktop computers, laptop computers, mobile devices,or the like.

In some embodiments, the communication network 110 represents one ormore computer networks (e.g., LAN, WAN, or the like). The communicationnetwork 110 may provide communication between any of the content capturesystems 102, the target systems 104, the content processing system 106,and the third-party systems 108. In some implementations, thecommunication network 110 comprises computing devices, routers, cables,buses, and/or other network topologies. In some embodiments, thecommunications network 110 may be wired and/or wireless. In variousembodiments, the communications network 110 may comprise the Internet,one or more networks that may be public, private, IP-based, non-IPbased, and so forth.

FIG. 2 depicts a block diagram 200 illustrating details of a contentcapture system 102 according to some embodiments. In some embodiments,the content capture system 102 includes a content capture module 202, ametadata capture module 204, a management module 206, a contentdatastore 208, a metadata datastore 210, a content and metadataprovisioning module 212, a communication module 214, and an optionalpresentation module 216.

The content capture module 202 may be configured to capture contentitems 218 of one or more targets. For example, the content capturemodule 202 may utilize one or more sensors (e.g., cameras, microphones,etc.) associated with the content capture system 102 to capture contentitems 218. In some embodiments, the one or more sensors are included inone or more devices performing the functionality of the content capturesystem 102, although in other embodiments, it may be otherwise. Forexample, the one or more sensors may be remote from the content capturesystem 102 and communicate sensor data (e.g., video, audio, images,pictures, etc.) to the content capture system 102 via the network 110.

The metadata capture module 204 may be configured to capture metadata220 associated with content items 218. For example, the metadata 220 mayinclude a location the content item 218 was captured, a time the contentitem 218 was captured, an identifier of the content capture system 102that captured the content item 218, and/or the like. In someembodiments, the metadata 220 may include an action request (e.g.,upload content item 218 to a third-party system 108). In someembodiments, the metadata 220 may be used to identify potentialstargets, actual targets, determine whether to distort particularfeatures within a content item 218, and so forth.

The management module 206 may be configured to manage (e.g., create,read, update, delete, or otherwise access) content items 218 stored atleast temporarily in the content datastore 208, and metadata 220 storedat least temporarily in the metadata datastore 210. The managementmodule 206 may perform any of these operations manually (e.g., by a userinteracting with a GUI), automatically (e.g., triggered by one or moreof the modules 212-214), or both. In some embodiments, the managementmodule 206 comprises a library of executable instructions which areexecutable by a processor for performing any of the aforementionedmanagement operations. The datastores 208-210 may be any structureand/or structures suitable for storing the content items 218 and themetadata 220. For example, the datastores 208-210, as well as some orall of the datastores described herein, may comprise a cache, a buffer,a relational database, an active database, a self-referential database,a table, a matrix, an array, a flat file, a documented-oriented storagesystem, a non-relational No-SQL system, and the like.

In some embodiments, the content items 218 include data of capturedcontent. For example, the data may correspond to pictures files, videofiles, audio files, and/or the like. In some embodiments, the data maycomprise a compressed format (e.g., JPEG) and/or a raw format.

In some embodiments, the metadata 220 may include a variety of data,attributes, and values associated with a content item 218. In someembodiments, the metadata 220 may be included within an associatedcontent item 218. In some embodiments, the metadata 220 may include someor all of the following data:

-   -   Content Item Identifier: an identifier of an associated content        item 218.    -   Content Capture System Identifier: an identifier (e.g., UID) of        the content capture system 102 that captured the associated        content item 218.    -   User Identifier: an identifier (e.g., UID) of a user of the        content capture system 102 that captured the associated content        item 218.    -   Content Item Type: identifies a content type of the content item        218, e.g., picture, video, audio, etc.    -   Location: a location where the associated content item 218 was        captured.    -   Time: a time (e.g., timestamp) the associated content item 218        was captured.    -   Action(s): one or more content item actions (or, “actions”)        associated with the content item 218. For example, actions may        include storing the content item 218 on the content capture        system 102, uploading the content item 218 to a third-party        system 108, and the like.

The content and metadata provisioning module 212 may be configured toprovide content items 218 and associated metadata 220. For example, themodule 212 may package a set of one or more content items 218 andassociated metadata 220, and transmit the package over a network (e.g.,network 110) to one or more other systems (e.g., the content processingsystem 106, social media system 108, etc.).

The communication module 214 may be configured to send requests, receiverequests, and/or otherwise provide communication with one or a pluralityof systems. In some embodiments, the communication module 214 may beconfigured to encrypt and decrypt communications. The communicationmodule 214 may send requests to and receive data from a system through anetwork or a portion of a network. Depending uponimplementation-specific or other considerations, the communicationmodule 214 may send requests and receive data through a connection, allor a portion of which may be a wireless connection. The communicationmodule 214 may request and receive messages, and/or other communicationsfrom associated systems.

The presentation module 216 may be configured to present content items218, present metadata 220, present a viewer to facilitate capturingcontent items 218, receive user input, search for particular contentitems 218 and metadata 220, and the like. In some embodiments, thepresentation module 216 may include a web browser interface or a mobileapplication interface.

FIG. 3 depicts a block diagram 300 illustrating details of a targetsystem 104 according to some embodiments. In some embodiments, thetarget system 104 include a location sensing module 302, a communicationmodule 304, and a target system datastore 306.

The location sensing module 302 may be configured to determine ageographic location of the target system 104. For example, locationinformation may be used to identify a set of potential target users, anda set of actual target users. In some embodiments, the location sensingmodule 304 may be implemented using GPS, Wi-Fi signals, and/or cellularsignals.

The communication module 304 may be configured to send requests, receiverequests, and/or otherwise provide communication with one or a pluralityof systems. In some embodiments, the communication module 304 may beconfigured to encrypt and decrypt communications. The communicationmodule 304 may send requests to and receive data from a system through anetwork or a portion of a network. Depending uponimplementation-specific or other considerations, the communicationmodule 304 may send requests and receive data through a connection, allor a portion of which may be a wireless connection. The communicationmodule 304 may request and receive messages, and/or other communicationsfrom associated systems. Received data may be stored in the datastore306.

The communication module 304 may also be configured to send locationand/or time information to the content processing system 106 on aperiodic basis, in response to trigger events, based on clockinformation, based on change of location, and/or the like.

In some embodiments, the target systems 104 include some or all of thefunctionality of the content capture systems 102, e.g., a presentationmodule, a content capture module, and the like.

FIG. 4 depicts a block diagram 400 illustrating details of a contentprocessing system 106 according to some embodiments. In someembodiments, the content processing system 106 includes a managementmodule 402, a content datastore 404, a metadata datastore 406, a profiledatastore 408, a recognizable characteristic datastore 410, a profilegeneration module 412, a location identification module 414, arecognizable characteristic generation module 418, a characteristicrecognition module 418, a distortion processing module 420, and acommunication module 422.

The management module 402 may be configured to manage (e.g., create,read, update, delete, or otherwise access) content items 218 stored atleast temporarily in the content datastore 404, metadata 220 stored atleast temporally in the metadata datastore 406, profiles 422 stored inthe profile datastore 408, and recognizable characteristics 424 storedin the recognizable characteristic datastore 410. The management module402 may perform any of these operations manually (e.g., by anadministrator interacting with a GUI), automatically (e.g., triggered byone or more of the modules 412-422), or both. In some embodiments, themanagement module 402 comprises a library of executable instructionswhich are executable by a processor for performing any of theaforementioned management operations. The datastores 404-410 may be anystructure and/or structures suitable for storing the content items 218,the metadata 220, the profiles 422, and recognizable characteristics424.

In some embodiments, the content items 218 and metadata 220 may only bestored temporarily by the content processing system 106, e.g., toprotect the privacy of associated users. For example, the content items218 and metadata 220 may only be stored long enough to perform theprocessing described herein (e.g., content item distortion, provision toone or more other systems, etc.), after which, the content items 218 andmetadata 220 may be deleted.

As mentioned above, in some embodiments, the content items 218 mayinclude data of captured content. Also as mentioned above, in someembodiments, the metadata 220 may include a variety of data, attributes,and values associated with a content item 218. In some embodiments, themetadata 220 may be included within an associated content item 218. Insome embodiments, the metadata 220 may include some or all of thefollowing data: a content item identifier, a content capture systemidentifier, a user identifier, a content item type, a location, a time,action(s), and the like.

In some embodiments, the profiles 424 may include a variety of data,attributes, and values associated with user profiles. For example,profiles 424 may be used to determine whether some, none, or all of theuser representations within a content item are distorted. In someembodiments, the profiles 424 may include some or all of the followingdata:

-   -   Profile Identifier: an identifier (e.g., UID) of the stored        profile 424.    -   Content Capture System Identifier: identifier(s) of one or more        content capture systems 102 associated the stored profile 424.    -   User Identifier: an identifier of a user associated with the        stored profile 424.    -   Time and Location: historical and current times (e.g.,        timestamp) and geographic locations (e.g., GPS coordinates) of        the associated target system 104. For example, times and        locations may be updated every 15 seconds, or at other        predetermined intervals.    -   Privacy Preferences: user-defined and/or default privacy        preferences to determine whether and/or how to distort a user's        representation in a content item 218. In some embodiments, the        privacy preferences may be associated with particular actions,        e.g., allow someone to take picture and store on phone, but        require distortion if the image is being published. In some        embodiments, the privacy preferences include a list or other        structure (collectively, a list) of trusted users, and one or        more actions permitted or not permitted for the trusted users.        For example, if a target user's representation is captured by a        content capture system 102 of a trusted user, the privacy        preferences may indicate that the content item 218 may be stored        and uploaded, stored but not uploaded, or the like.

Similarly, in some embodiments, the privacy preferences include a listof untrusted users, and one or more actions permitted or not permittedfor the untrusted users. For example, if a target user's representationis captured by a content capture system 102 of an untrusted user, theprivacy preferences may indicate that the content item 218 may not bestored nor uploaded.

In some embodiments, the privacy preferences include a list of trustedlocations, and one or more actions permitted or not permitted for thetrusted locations. For example, if a target user's representation iscaptured by a content capture system 102 within a range (e.g., 25 m) ofa trusted location, the privacy preferences may indicate that thecontent item 218 may be stored and uploaded, stored but not uploaded, orthe like.

Similarly, in some embodiments, the privacy preferences include a listof untrusted locations, and one or more actions permitted or notpermitted for the untrusted locations. For example, if a target user'srepresentation is captured by a content capture system 102 within arange (e.g., 25 m) of an untrusted location, the privacy preferences mayindicate that the content item 218 may not be stored nor uploaded.

In some embodiments, the privacy preferences include a list of trustedtimes, and one or more actions permitted or not permitted for thetrusted times. For example, if a target user's representation iscaptured by a content capture system 102 within an amount of time (e.g.,30 m) of a trusted time (e.g., 6:00 PM), the privacy preferences mayindicate that the content item 218 may be stored and uploaded, storedbut not uploaded, or the like.

Similarly, in some embodiments, the privacy preferences include a listof untrusted times, and one or more actions permitted or not permittedfor the untrusted times. For example, if a target user's representationis captured by a content capture system 102 within an amount of time(e.g., 30 m) of an untrusted time (e.g., 1:00 AM), the privacypreferences may indicate that the content item 218 may, the privacypreferences may indicate that the content item 218 may not be stored noruploaded.

In some embodiments, some or all privacy preferences may be enabled ordisabled, e.g., toggled between “on” or “off” For example, a particularprivacy preference, e.g., a untrusted location preference, may be turnedoff, thereby allowing content capture systems 102 to store and/orprovide content items including their representation without distortion,which would otherwise not be allowed if the untrusted locationpreference was turned on.

In some embodiments, the recognizable characteristics 426 may include avariety of data, attributes, and values. For example, user profiles maybe used to determine whether some, none, or all of the userrepresentations within a content item are distorted. In someembodiments, the recognizable characteristics 426 may include some orall of the following data:

-   -   Recognizable Characteristic Identifier: identifies the stored        recognizable characteristics 426.    -   Recognizable Characteristic: the recognizable characteristic.        For example, a set of images of the associated user, a composite        image, or other data that may be used to identify a        representation of the associated user within a content item 218.    -   Profile: identifies an associated profile 424.

The profile generation module 412 may be configured to generate profiles424. In some embodiments, profiles may be generated during a useraccount registration process. For example, the profile generation module412 may collect user provided information (e.g., privacy preferences)and system provided information (e.g., content capture systemidentifier, etc.). In some embodiments, the profile generation module412 may be configured to update profiles 424. For example, profiles 424may updated to include a new locations and times, different privacypreferences, and so forth.

The location identification module 414 may be configured to determine alocation of users and/or systems that capture content items 218, andusers and/or systems that are the target of content capture systems 102.For example, the location identification module 414 may interpretmetadata 220 to identify a location of a content capture system 102 anda time the content item 218 was captured, and also identify a set ofpotential targets within a range of the content capture system 102 atthe time content item 218 was captured. In some embodiments, thelocation identification module 414 may be configured to identify the setof potential targets by retrieving selected profiles 424 having a timeand location with a range of the time and location indicated in theassociated metadata 220, and generate a set of user identifiers and/ortarget system 104 identifiers from the selected profiles 424.

In some embodiments, the location identification module 414 determineslocation through one or more positioning techniques. For example, thelocation identification module 414 may determine the location throughGPS tracking of the devices associated with content capture systems 102and target systems 104. In some embodiments, the location identificationmodule 414 may determine location based on Wi-Fi and/or cellular signalssent to and received from the devices associated with the contentcapture systems 102 and target systems 104.

The recognizable characteristics generation module 416 may be configuredto generate recognizable characteristics 426 for an individual. Therecognizable characteristics 426 may be any characteristics throughwhich an individual may be identified or associated. In being associatedwith an individual, a characteristic may allow for an individual to beidentified out of a group of individuals. For example, the recognizablecharacteristics 426 may be a wearable item, such as an article ofclothing, a pair of sun-glasses, or an emblem. In some embodiments, therecognizable characteristics 426 are characteristics that are determinedthrough facial recognition techniques. For example, the recognizablecharacteristics 426 may be the shape of the face, the eyes, the nose, orthe chin of an individual. The facial recognition techniques may includetechniques for converting a three dimensional profile of an individualcontained within an image to a two dimensional profile, from whichrecognizable characteristics 426 may be determined.

The recognizable characteristics generation module 416 may be configuredto generate recognizable characteristics 426 from images that arereceived from the individual or a person or user associated with theindividual. The images can be received from the target system 104. Inone example, the recognizable characteristics generation module 416 maydetermine the characteristics from six images that are received from thetarget system 104. The six images may include, for example, a closeimage (e.g., 2 feet or less from the individual) of the face andprofiles of the individual, a far range (e.g., 10 feet or more from theindividual) of the face and profiles of the individual, and so forth.

The recognizable characteristics generation module 416 may be configuredto associate the recognizable characteristics 426 of an individual withan identifier that represents the individual and/or a target system 104or content capture system 102 that the individual uses. In associatingthe recognizable characteristics 426 of an individual with an identifierthat represents the individual, the recognizable characteristicsgeneration module 416 may generate or modify a data structure uniquelyrepresenting the individual to include the identifier and therecognizable characteristics 426. Additionally, the recognizablecharacteristics generation module 416 may generate or modify anindividual's data structure to include the images that were used todetermine the recognizable characteristics 426. The data structurerepresenting the individual may be stored in the recognizablecharacteristics datastore 410.

The characteristic recognition module 418 may be configured to determinewhether a representation of a potential target user is included within acontent item 218. For example, the characteristic recognition module 418may compare the recognizable characteristic 426 of each potential targetusers with the content item 218, and flag any matches as actual targetusers. In some embodiments, the characteristic recognition module 418determines whether or not content items 218 contain recognizablecharacteristics 426 of a potential target user represented by the datastructure stored in the recognizable characteristics datastore 410 thatincludes the recognizable characteristics 426.

In some embodiments, the characteristics recognition module 418 mayperform image processing on the content item 218 to determine whetherrecognizable characteristics 426 are present in the content item 218.For example, the characteristics recognition module 418 may convert thecontent item 218 to gray scale wherein each pixel is represented by asingle intensity value. The characteristics recognition module 410 maydetermine whether a recognizable characteristic 426 is present in thecontent item 218, for example, through pixel matching. For example, thecharacteristics recognition module 418 may determine whether or not thepixels that make up the recognizable characteristic 426 are present inthe same order as in the recognizable characteristic 426 in the contentitem 218. The characteristics recognition module 418 may use a minimumthreshold to determine whether a recognizable characteristic 426 ispresent in the content item 218 through pixel matching. For example, ifthe characteristics recognition module 418 determines that a specificnumber of pixels, e.g. seventy five percent, of the recognizablecharacteristic 426 is found in the content item 218 in the order thatthey exist in the recognizable characteristic 426, then thecharacteristics recognition module 418 may determine that therecognizable characteristic 426 is present in the content item 218.

The distortion processing module 420 may be configured to evaluatewhether to distort a content item 218 and to distort at least a portion(e.g., a feature of a representation of user within the content item218) of the content item 218 if the characteristics recognition module418 determines the content item 218 contains a recognizablecharacteristic 426 of a potential target user, and if the privacypreferences of the recognized target user indicates it should bedistorted. In distorting a content item 218, the distortion processingmodule 420 may use the privacy preferences of the actual target users(i.e., the subset of users of the set of potential users that includedwithin the content item 218). For example, the distortion processingmodule 420 may blur, or otherwise obscure, the face or other feature ofthe representation of the actual target user.

Additionally, the distortion processing module 420 may be configured toonly distort the content item 218 if certain conditions specified in theprivacy preferences are met. For example, if the privacy preferencesindicate to only distort the content item 218 if a user is trying topost the content item 218 to a third-party system 108, the distortionprocessing module 420 may only distort the content item 218 if a userattempts to post the content item 218 a third-party system 108.

As indicated above, the distortion processing module 420 may blurfeatures of actual target user representations in a content item 218.For example, the distortion processing module 420 may apply a Gaussianblurring function to the specific pixels in the content item 218 thatform the representation of the actual target user or any other featurethrough which the target user may be identified. In some embodiments,the distortion processing module 420 may continue to apply a Gaussianblurring function to the specific pixels in the content item 218 untilthe representation of the actual target user or any other featuresthrough which the actual target user may be identified are no longerrecognizable in the content item 218.

The communication module 422 may be configured to provide and receivecontent items 218 (distorted and/or undistorted), send requests, receiverequests, and/or otherwise provide communication with one or a pluralityof systems. In some embodiments, the communication module 422 may beconfigured to encrypt and decrypt communications. The communicationmodule 422 may send requests to and receive data from a system through anetwork or a portion of a network. Depending uponimplementation-specific or other considerations, the communicationmodule 422 may send requests and receive data through a connection, allor a portion of which may be a wireless connection. The communicationmodule 422 may request and receive messages, and/or other communicationsfrom associated systems.

FIG. 5 depicts a flowchart 500 illustrating a method of distorting acontent item 218 (e.g., a picture) according to some embodiments. Inthis and other flowcharts, the flowchart shows by way of example asequence of steps. It should be understood the steps may be reorganizedfor parallel execution, or reordered, as applicable. Moreover, somesteps that could have been included may have been removed to avoidproviding too much information for the sake of clarity and some stepsthat were included could be removed, but may have been included for thesake of illustrative clarity.

In step 502, a content capture module 202 of a content capture system102 captures a content item 218 and associated metadata 220. Forexample, a content capture system 102 may capture a picture of one ormore individuals, and capture a time and location the picture was taken.

In step 504, a management module 206 of the content capture system 102stores the content item 218 in a content datastore 208, and stores themetadata 220 in a metadata datastore 210.

In step 506, a content and metadata provisioning module 212 of thecontent capture system 102 provides the content item 218 and associatedmetadata 220 to a content processing system 106. For example, thecontent and metadata provisioning module 212 may provide the contentitem 218 and metadata 220 in response to a particular action (e.g.,storing the content item 218 on the content capture system 102). In someembodiments, a communication module 422 of the content processing system106 may receive the content item 218 and metadata 220 over a network110.

In step 508, communication module(s) 306 of one or more targets systems104 provide current location(s) for the one or more target systems 104.In some embodiments, location sensing modules 302 of the one or moretarget system 104 determine the current location(s). It will beappreciated that this step, as with other steps, may be performedmultiple times and/or at different points of the method. For example,this step may be performed at predetermined intervals (e.g., every 15seconds). In some embodiments, the target systems 104 may broadcast thelocations at various predetermined intervals, and/or provide thelocation in response to a request from the content processing system106.

In step 510, a location identification module 414 of the contentprocessing system 106 identifies a time and location based on theassociated metadata 220. For example, the location identification module414 may perform the determination based on timestamp data and GPScoordinate data included in the metadata 220.

In step 512, the location identification module 414 of the contentprocessing system 106 identifies a set of potential target users withina predetermined range of the location. For example, the locationidentification module 414 may retrieve selected profiles 424 of fivedifferent potential target users that have a time and location within apredetermined range of the time and location included in the metadata220.

In step 514, a characteristic recognition module 418 of the contentprocessing system 106 identifies at least one actual target user in thecontent item 218. In some embodiments, the characteristic recognitionmodule 418 compares recognizable characteristics 426 of the potentialtarget users with representations of the individuals within the contentitem 218. For example, the potential target users having a recognizablecharacteristic 426 matching a representation in the content item 218 maybe flagged as actual target users.

In step 516, a distortion module 420 of the content processing system106 determines whether to distort at least a portion of the content item218. For example, the characteristic recognition module 418 mayrecognize three actual target users from the set of potential targetusers. The distortion module 420 may individually determine based oncorresponding privacy preferences whether to distort the representationsof the actual target users within the content item 218. For example,distortion module 420 may indicate the face of the representation of afirst actual target user may be distorted based on the privacypreferences of the first actual target user, while the remainingrepresentations of the other actual target users may not be distortedbased on the preferences of the second and third actual target users.

In step 518, the distortion module 420 of the content processing system106 distorts a feature of each of the one or more representations of theleast one actual target user based on the determination. Continuing theexample above, the distortion module 420 may blur the face of the firstactual target user, while the representations of the of the other actualtarget users remain in their original form.

In step 520, a communication module 422 of the content processing system106 provides the distorted content item 218 to the content capturesystem 102. In some embodiments, a communication module 214 of thecontent capture system 102 receives the distorted content item 218 overthe network 110.

In step 522, the management module 206 of the content capture system 102replaces the corresponding non-distorted content item 218 with thedistorted content item 218.

FIG. 6 depicts a flowchart 600 illustrating a method of distorting acontent item (e.g., a picture) and posting the distorted content item218 to a third-party system 108 (e.g., a social media system) accordingto some embodiments.

In step 602, a metadata capture module 204 of a content capture system102 requests a content item action. For example, a content item actionmay comprise storing a content item 218, uploading a content item 218,and so forth. For the purposes of this example, the content item actionrequest comprises a request to upload a content item 218 to a socialmedia system 108.

In step 604, a content and metadata provisioning module 212 of thecontent capture system 102 provides the content item 218 and associatedmetadata 220 to the third-party system 108 indicated by the content itemaction request. For example, the content item 218 and metadata 220 maybe transmitted over a network 110. In some embodiments, the content itemaction request may be included in the metadata 220.

In step 606, the third-party system 108 provides (or, redirects) thecontent item 218 and metadata 218 to a content processing server 106.

In step 608, communication module(s) 306 of one or more targets systems104 provide current location(s) for the one or more target systems 104.In some embodiments, location sensing modules 302 of the one or moretarget systems 104 determine the locations. It will be appreciated thatthis step, as with other steps, may be performed multiple times and/orat different points of the method. For example, this step may beperformed at predetermined intervals (e.g., every 15 seconds). In someembodiments, the target systems 104 may broadcast their locations atvarious predetermined intervals, and/or provide their location inresponse to a request from the content processing system 106.

In step 610, a location identification module 414 of the contentprocessing system 106 identifies a time and location based on theassociated metadata 220. For example, the location identification module414 may perform the determination based on timestamp data and GPScoordinate data included in the metadata 220.

In step 612, the location identification module 414 of the contentprocessing system 106 identifies a set of potential target systems 104within a predetermined range of the location. For example, the locationmodule 414 may retrieve selected profiles 424 of five differentpotential target users that have a time and location within apredetermined range of the time and location included in the metadata220.

In step 614, a characteristic recognition module 418 of the contentprocessing system 106 identifies at least one actual target user in thecontent item 218. In some embodiments, the characteristic recognitionmodule 418 compares recognizable characteristics 426 of the potentialtarget users with representation of individuals within the content item218. For example, the potential target users having a recognizablecharacteristic 426 matching a representation in the content item 218 maybe flagged as an actual target user.

In step 616, a distortion module 420 of the content processing system106 determines whether to distort at least a portion of the content item218. For example, the characteristic recognition module 418 mayrecognize three actual target users from the set of potential targetusers. The distortion module 420 may individually determine based oncorresponding privacy preferences whether to distort the representationsof the actual target users within the content item 218. For example, thedistortion module 420 may indicate the face of the representation of afirst actual target user may be distorted based on the privacypreferences of the first actual target user, while the remainingrepresentations may not be distorted based on the preferences of thesecond and third actual target users.

In step 618, the distortion module 420 of the content processing system106 distorts a feature of each of the one or more representations of theleast one actual target user based on the determination. Continuing theexample above, the distortion module 420 may blur the face of the firstactual target user, while the representations of the of the other actualtarget users may remain in their original form.

In step 620, a communication module 422 of the content processing system106 provides the distorted content item 218 to the third-party system108. In step 622, the third-party system 108 posts (or, “publishes”) thecontent item 218. For example, the content item 218 may be posted on aFacebook user's wall or timeline.

FIG. 7 depicts a flowchart 700 illustrating a method of operation of acontent processing system 106 for distorting a content item 218according to some embodiments.

In step 702, a communication module 422 receives a picture 218 andassociated metadata 220, the picture 218 and the associated metadata 220captured by a content capture system 102. In step 704, a recognizablecharacteristic datastore 410 stores a plurality of recognizablecharacteristics 424, each of the plurality of recognizablecharacteristics 424 associated with a different user 104. In step 706, alocation identification module 414 identifies a location based on theassociated metadata 220. In step 708, the location identification module414 identifies a set of potential target systems 104 within apredetermined range of the location. In step 710, a characteristicrecognition module 418 retrieves, based on the identified target systems104, a set of recognizable characteristics from the recognizablecharacteristics datastore 410. In step 712, the characteristicrecognition module 418 compares the set of recognizable characteristicsof the plurality of recognizable characteristics with the picture, eachrecognizable characteristic of the set of recognizable characteristicsassociated with a different potential target user of a correspondingpotential target system. In step 714, the characteristic recognitionmodule 418 determines whether the picture includes one or morerepresentations of at least one actual target user of the potentialtarget users based on the comparison. In step 716, a distortion module420 distorts a feature of each of the one or more representations of theleast one actual target user in response to the determination. In step718, a communication module 422 provides the distorted picture to thefirst content capture system 102

FIG. 8 depicts a block diagram 800 illustrating details of a computingdevice 802 according to some embodiments. Any of the content capturesystems 102, the target systems 104, the content processing system 106,the third-party systems 108, and the communication network 110 maycomprise an instance of the digital device 802. The digital device 802comprises a processor 804, memory 806, storage 808, an input device 810,a communication network interface 812, and an output device 814communicatively coupled to a communication channel 816. The processor804 is configured to execute executable instructions (e.g., programs).In some embodiments, the processor 804 comprises circuitry or anyprocessor capable of processing the executable instructions.

The memory 806 stores data. Some examples of memory 806 include storagedevices, such as RAM, ROM, RAM cache, virtual memory, etc. In variousembodiments, working data is stored within the memory 806. The datawithin the memory 806 may be cleared or ultimately transferred to thestorage 808.

The storage 808 includes any storage configured to retrieve and storedata. Some examples of the storage 808 include flash drives, harddrives, optical drives, and/or magnetic tape. Each of the memory system806 and the storage system 808 comprises a computer-readable medium,which stores instructions or programs executable by processor 804.

The input device 810 is any device that inputs data (e.g., mouse andkeyboard). The output device 814 outputs data (e.g., a speaker ordisplay). It will be appreciated that the storage 808, input device 810,and output device 814 may be optional. For example, therouters/switchers may comprise the processor 804 and memory 806 as wellas a device to receive and output data (e.g., the communication networkinterface 812 and/or the output device 814).

The communication network interface 812 may be coupled to a network(e.g., network 110) via the link 818. The communication networkinterface 812 may support communication over an Ethernet connection, aserial connection, a parallel connection, and/or an ATA connection. Thecommunication network interface 812 may also support wirelesscommunication (e.g., 802.11 a/b/g/n, WiMax, LTE, WiFi). It will beapparent that the communication network interface 812 may support manywired and wireless standards.

It will be appreciated that the hardware elements of the digital device802 are not limited to those depicted in FIG. 8 . A digital device 802may comprise more or less hardware, software and/or firmware componentsthan those depicted (e.g., drivers, operating systems, touch screens,biometric analyzers, or the like). Further, hardware elements may sharefunctionality and still be within various embodiments described herein.In one example, encoding and/or decoding may be performed by theprocessor 804 and/or a co-processor located on a GPU (i.e., NVidia).

It will be appreciated that a “module,” “system,” “datastore,” and/or“database” may comprise software, hardware, firmware, and/or circuitry.In one example, one or more software programs comprising instructionscapable of being executable by a processor may perform one or more ofthe functions of the modules, datastores, databases, or systemsdescribed herein. In another example, circuitry may perform the same orsimilar functions. Alternative embodiments may comprise more, less, orfunctionally equivalent modules, systems, datastores, or databases, andstill be within the scope of present embodiments. For example, thefunctionality of the various systems, modules, datastores, and/ordatabases may be combined or divided differently.

The present invention(s) are described above with reference to exampleembodiments. It will be apparent to those skilled in the art thatvarious modifications may be made and other embodiments may be usedwithout departing from the broader scope of the present invention(s).Therefore, these and other variations upon the example embodiments areintended to be covered by the present invention(s).

The invention claimed is:
 1. A system, comprising: a communicationmodule configured to receive a picture and associated metadata capturedby a content capture system, the associated metadata including a picturetime when the picture was taken and a picture location where the picturewas taken, the picture possibly including a captured representation of atarget user; and a recognizable characteristic datastore configured tostore recognizable characteristics of a plurality of target users, therecognizable characteristics of each respective target user of theplurality of target users capable of assisting in identifying capturedrepresentations of the respective target user in pictures, eachrespective target user of the plurality of target users associated witha respective mobile device; the system being configured to receivetarget locations of each respective mobile device associated with eachrespective user of the plurality of target user at predeterminedintervals; a module configured to: identify from the associated metadatathe picture time when the picture was taken and the picture locationwhere the picture was taken, and evaluate the target locations of theplurality of mobile devices associated with the plurality of targetusers to identify any particular mobile devices that were at or near thepicture location at or near the picture time to identify a set of one ormore potential target users of the plurality of target users who mighthave been captured in the picture; and a characteristic recognitionmodule configured to: retrieve the recognizable characteristics of eachpotential target user of the set of one or more potential target userswho might have been captured in the picture, and evaluate the picture totry to identify any captured representation of any potential target userof the set of one or more potential target users who was captured in thepicture, by searching the picture for the recognizable characteristicsof each potential target user of the set of one or more potential targetusers who might have been captured in the picture; a datastoreconfigured to store user preferences of each respective target user ofthe plurality of target users, the user preferences defining when therespective target user of the plurality of target users wishes todistort or wishes not to distort captured representations of therespective target user of the plurality of target users in pictures, theuser preferences comprising one or more locations and/or one or moretimes; and a processing module configured to: retrieve the userpreferences of any potential target user of the set of one or morepotential target users who was identified as captured in the picture,determine whether the picture time when the picture was taken is withinan amount of time of one of the one or more times comprised by the userpreferences of any potential target user of the set of one or morepotential target users who was identified as captured in the pictureand/or whether the picture location where the picture was taken iswithin a range of a location of the one or more locations comprised bythe user preferences of any potential target user of the set of one ormore potential target users who was identified as captured in thepicture, and in response to the determination, initiate a process tomodify the at least a portion of the captured representation of at leastone potential target user of the set of one or more potential targetusers who was identified as captured in the picture, the communicationmodule further configured to communicate at least a portion of themodified picture to a computer network.
 2. The system of claim 1,wherein at least one of the recognizable characteristics comprises oneor more images.
 3. The system of claim 1, wherein at least one of therecognizable characteristics is derived from one or more images.
 4. Thesystem of claim 1, wherein at least one of the recognizablecharacteristics comprises a wearable item.
 5. The system of claim 1,wherein the communication module is further configured to communicatethe at least a portion of the modified picture to the content capturesystem.
 6. The system of claim 1, wherein the at least a portion of themodified picture comprises one or more facial features.
 7. The system ofclaim 1, further comprising a profile generation module configured todetermine user preferences for the at least one potential target user ofwhich captured representation has been identified in the picture throughthe evaluation.
 8. The system of claim 1, wherein the processing moduleis configured to blur the at least a portion of the capturedrepresentation.
 9. A method, comprising: receiving a picture andassociated metadata, the picture and the associated metadata captured bya content capture system, the associated metadata including a picturetime when the picture was taken and a picture location where the picturewas taken, the picture possibly including a captured representation of atarget user; storing recognizable characteristics of a plurality oftarget users, the recognizable characteristics of each respective targetuser of the plurality of target users capable of assisting inidentifying captured representations of the respective target user inpictures, each respective target user of the plurality target of usersassociated with a respective mobile device; receiving target locationsof each respective mobile device associated with each respective targetuser of the plurality of target users at predetermined intervals;identifying from the associated metadata the picture time when thepicture was taken and the picture location where the picture was taken;evaluating the target locations of the plurality of mobile devicesassociated with the plurality of target users to identify any particularmobile devices that were at or near the picture location at or near thepicture time to identify a set of one or more potential target users ofthe plurality of target users who might have been captured in thepicture; retrieving the recognizable characteristics of each potentialtarget user of the set of one or more potential target users who mighthave been captured in the picture; evaluating the picture to try toidentify any captured representation of any potential target user of theset of one or more potential target users who was captured in thepicture, by searching the picture for the recognizable characteristicsof each potential target user of the set of one or more potential targetusers who might have been captured in the picture; storing userpreferences of each respective target user of the plurality of targetusers, the user preferences defining when the respective target user ofthe plurality of target users wishes to distort or wishes not to distortcaptured representations of the respective target user of the pluralityof target users in pictures, the user preferences comprising one or morelocations and/or one or more times; retrieving the user preferences ofany potential target user of the set of one or more potential targetusers who was identified as captured in the picture; determining whetherthe picture time when the picture was taken is within an amount of timeof one of the one or more times comprised by the user preferences of anypotential target user of the set of one or more potential target userswho was identified as captured in the picture and/or whether the picturelocation where the picture was taken is within a range of a location ofthe one or more locations comprised by the user preferences state of anypotential target user of the set of one or more potential target userswho was identified as captured in the picture; in response to thedetermination, initiating a process to modify the at least a portion ofthe captured representation of at least one potential target user of theset of one or more potential target users who was identified as capturedin the picture through the evaluation; and providing at least a portionof the modified picture to a computer network.
 10. The method of claim9, wherein at least one of the recognizable characteristics comprisesone or more images.
 11. The method of claim 9, wherein at least one ofthe recognizable characteristics is derived from one or more images. 12.The method of claim 9, wherein at least one of the recognizablecharacteristics comprises a wearable item.
 13. The method of claim 9,wherein the at least a portion of the modified picture is provided tothe content capture system.
 14. The method of claim 9, wherein the atleast a portion of the modified picture comprises one or more facialfeatures.
 15. The method of claim 9, further comprising determining userpreferences for the at least one potential target user of which capturedrepresentation has been identified in the picture through theevaluation.
 16. The method of claim 9, wherein the initiating a processto modify includes initiating a process to blur the at least a portionof the captured representation.